Professional video cameras typically have three sensors to collect light, each filtered for red, green, and blue channels. Digital still photography typically does not employ a three-sensor design; digital still photography instead uses a single sensor design with individual pixels filtered for red, green, and blue (or other color primaries such as magenta, cyan and yellow.) This single-sensor color design is sometimes called a Bayer sensor, which is common in nearly all digital still cameras, both professional and consumer models. As the spatial resolution of video increases, there are numerous benefits in switching to the single-sensor Bayer design—as observed in some very high-end digital cinema cameras used for movie acquisition. Yet traditionally there are post-production workflow issues that arise when applying Bayer sensors to video applications.
Notably, image data collected from Bayer-pattern imagers (also known as RAW images) is neither YUV nor RGB, the most common color orientation expected by traditional post-production tools. This is true for both still cameras and emerging digital cinema cameras. This characteristic demands that existing industry tools either be “upgraded” so they are compatible with RAW images, or that new utilities be written that convert RAW images into traditional planar color spaces compatible with existing industry tools. The most common workflow employed by the industry today is to arithmetically convert RAW images into planar RGB images before common operations are performed, such as applying a saturation matrix or white balance, which is then followed by compressing or encoding the result into a smaller file size.
In order to extract full spatial and color information from a RAW image, a highly compute-intensive operation known as a “demosaic filter” must first be applied to each RAW image. The demosaic operation interpolates missing color primaries at each pixel location, as Bayer sensors only natively provide one primary color value per pixel location. These operations are generally performed by special algorithms residing inside the camera. In this situation the RAW image is never presented to the user, but instead the “developed” YUV or RGB image is presented to the user from the camera after internal processing, sometimes in the form of a compressed JPEG (or other compressed format) image. In the case of RAW modes on digital still cameras, some camera processing is delayed and performed outside the camera (most notably the compute-intensive demosaic processing). In this case the unprocessed RAW image is presented to the user from the camera, but prior to traditional YUV or RGB processing the demosaic (also known as de-Bayer) filter still must first be applied to the RAW image, but is done so outside the camera, yet the processing order described remains the same. The “developed” output of the de-Bayer filter operation is a planar image, usually RGB, but may also be other color primaries instead. A filter to correct color and contrast (compensating for sensor characteristics) is then applied to the planar image. Typically the planar image color space is further converted to a more compressible form such as YUV (common for DV, JPEG, or MPEG compression). The YUV image is compressed for delivery or storage, whether inside the camera or performed as a second step outside the camera.
In the RAW mode, some digital still cameras allow preprocessed sensor data to be written to the file along with metadata describing the cameras settings. A still-camera RAW mode does not achieve the workflow benefits described here, as it does not allow easy or fast previews, and the images can only be displayed by tools designed to understand the RAW format from Bayer-pattern imagers.